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Found 13,479 Skills
Carve guardrail-adjacent items out of scope with safe alternatives before risk-adjacent work starts, then run the safe remainder at full strength in a fresh subagent that only ever sees the carved prompt, never the risky input. Use when a task includes stealth, scraping, privacy, IP, policy, licensing, security, or other safety-adjacent material that could be silently dropped, over-elaborated, or needlessly diluted. Fires on the impulse, not only the topic: the moment you notice yourself about to hedge, soften, silently skip, or brace for a refusal, carve before you execute.
Break down complex tasks into atomic, actionable goals with clear dependencies and success criteria. Use when planning multi-step projects, coordinating agents, or decomposing complex requests.
Generate a portable, self-contained Agent Skill from mature, curated Obsidian wiki pages — turning a cluster of verified knowledge into a reusable "digital expert" (SKILL.md + references/). Use this skill when the user says "/vault-skill-factory", "make a skill from my wiki", "turn these pages into a skill", "generate an agent skill from my vault", "package my notes on X as a skill", "build a domain-expert skill from my wiki", or wants to distill recurring, mature wiki knowledge into a shareable skill. Inspired by OpenKB's "drop in a book → out comes a digital expert" pattern. The factory ONLY reads the vault and WRITES TO A REVIEW DIRECTORY — it never installs skills, never writes into .skills/, and never touches global skill directories.
Controls a cloud browser from a sandboxed remote machine. Use when the agent is running in a sandbox (no GUI) and needs to navigate websites, interact with web pages, fill forms, take screenshots, or expose local dev servers via tunnels.
Design and build multi-agent harness architectures for long-running AI application development. GAN-inspired Generator-Evaluator pattern, Sprint Contract negotiation, context management, quality criteria calibration. Based on Anthropic Engineering patterns. Use when: "build a harness", "multi-agent architecture", "agent orchestration", "generator-evaluator", "long-running app", "harness design", "agent pipeline", "quality evaluation loop", "sprint contract", "build app with agents", "Claude Agent SDK architecture", or when building complex full-stack apps that need planning → generation → evaluation cycles. Also use when discussing context degradation, self-evaluation bias, or assumption testing in AI workflows.
End-to-end Swiggy ordering with Prava card-token checkout. Use when the user wants an AI agent to set up Swiggy MCP, browse/search Swiggy Food/Instamart/Dineout, choose a saved delivery address, add or review Swiggy cart items, create a Prava authorization/payment session, and complete Swiggy checkout using Prava-issued tokenized card credentials. Also use when the user asks to install or configure the Swiggy MCP plus Prava payment flow for agentic purchases.
Use when the user asks for a code review by a fleet of specialized reviewer agents, wants multiple independent reviewer perspectives, or asks to run reviewers in single-pass or iterative fix-until-clean mode. Launches focused subagents for correctness, security, architecture, conventions, simplicity, UX, reliability, telemetry, testing, compatibility, and documentation review.
Automate 7-phase feature development with specialized agents (code-explorer, code-architect, code-reviewer). Use for multi-file features, architectural decisions, or encountering ambiguous requirements, integration patterns, design approach errors.
Set up, supervise, and control a persistent multi-layer "explore → execute → escalate" agent loop on a project. Use whenever a user asks to keep an agent running on a task across sessions or days — finding bugs, polishing writing, distilling a style, watching feeds, scanning for gaps, or any task whose value grows with how many findings the agent produces. Also use when the user wants to inspect, pause, resume, stop, or send a new instruction to an already-running perpetuum task.
Bridge Claude Code auto-memory into AgentDB with ONNX embeddings, deduplicate, and enable unified cross-project search
Guidelines for creating well-structured AI agent skills. Use when building a new skill, reviewing skill quality, or unsure how to organize a skill.
Connect OpenClaw AI agents to DingTalk with message handling, document operations, calendar, todos, and AI cards